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Documentation Index

Fetch the complete documentation index at: https://docs.conformly.ai/llms.txt

Use this file to discover all available pages before exploring further.

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Supported formats

Conformly accepts:
FormatUse case
PDFThe most common — system requirements specs, software requirements specs, architecture documents, test plans, audit reports.
DOCXMicrosoft Word documents. Same use cases as PDF.
XLSXSpreadsheets — typically requirements matrices or traceability tables.
ReqIF / XMLDOORS, Polarion, codebeamer exports.
CSVBulk requirement lists, gap inventories.
The upload size limit is 100 MB per file. If you need to analyze a larger document, split it first.

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The upload flow

The simplest path is the New Analysis page:
1

Sidebar → New Analysis

Lands you on a clean drop zone.
2

(Optional) Pick a product to tag uploads with

If you have products defined in your workspace, a small picker appears above the dropzone. Pick one and every dropped file inherits that product.
3

Drag files into the dropzone, or click 'Browse files'

You can drop multiple files at once. Each file gets its own row in the staging area below the dropzone.
4

Watch the per-file status indicators

Each row goes through uploading → classifying → ready automatically. The whole flow takes 5–15 seconds for a typical document.
You can also upload from the Work Products page if you want to add documents without immediately analyzing them. Same dropzone, same flow — just no Analyze button at the end.

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What happens during upload

Conformly does five things between “you drop the file” and “the file is ready to analyze”:
  1. Stream the file to secure object storage. The bytes never sit on a Conformly-controlled disk.
  2. Run the parser. PDFs go through Landing AI Vision (page-aware, high-fidelity) when available, with PyMuPDF and pypdf as fallbacks. DOCX/XLSX use their native parsers. ReqIF/XML use a structured parser.
  3. Extract page-level chunks so findings can later cite exact pages.
  4. Auto-classify the document. The classifier reads the parsed text and decides whether this is a system requirements spec, a software requirements spec, an architecture document, a test plan, etc., and suggests which standards to evaluate it against.
  5. Cache the parsed content in storage. Re-uploads of the same file (matched by content hash) skip parsing entirely and become near-instant.

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Auto-classification

The classifier picks one of these V-Model categories:
  • Requirements (system requirements, stakeholder requirements, software requirements)
  • Architecture (system architecture, software architecture, detailed design)
  • Testing (unit test plans, integration test reports, validation reports)
  • Documentation (manuals, design notes, anything that doesn’t fit the V-Model)
Then it suggests one or more standards to evaluate against, based on the content:
  • ASPICE 3.1 for general process compliance
  • ISO 26262 for safety-relevant content
  • ISO 21434 for cybersecurity-relevant content
You can override the classifier’s choices before clicking Analyze. The suggested standards appear as checkboxes — uncheck the ones you don’t want, or pick a different category from the dropdown. If auto-classification fails (the document is image-only, encrypted, or genuinely unclassifiable), the row turns yellow and the error message tells you to pick standards manually.

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Re-uploading a document (versioning)

If you upload a newer version of a document Conformly has already analyzed, the platform detects it via content hash and offers to re-analyze with change detection. The old findings are preserved (marked as “from previous version”) and a new analysis runs against the new version. This is how you track gap closure over time — the audit-readiness score moves up as gaps disappear from successive versions of the same document.

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Common upload problems

SymptomCauseFix
”File too large” toastDocument exceeds 100 MBSplit the document or compress its embedded images
”Auto-classification failed”Document is image-only or encryptedRun OCR locally and re-upload, or pick standards manually
”Parsed content insufficient”Parser returned fewer than 50 characters of textSame as above — likely a scanned PDF without OCR
Upload progress stuck at 0%Network/CORS issueCheck the browser dev tools console for the actual error
Upload succeeds but classification 422sBackground parser is still runningWait 5–10 seconds and click Retry — the server polls for parsed content with a 6-second budget